AlphaGo Zero Explained In One Diagram
Download the AlphaGo Zero cheat sheet
Get the full cheat sheet here
Recently Google DeepMind announced AlphaGo Zero — an extraordinary achievement that has shown how it is possible to train an agent to a superhuman level in the highly complex and challenging domain of Go, ‘tabula rasa’ — that is, from a blank slate, with no human expert play used as training data.
It thrashed the previous reincarnation 100–0, using only 4TPUs instead of 48TPUs and a single neural network instead of two.
Want to quickly learn how it works? Look no further…
The AlphaGo Zero cheat sheet
The paper that the cheat sheet is based on was published in Nature and is available here. I highly recommend you read it, as it explains in detail how deep learning and Monte Carlo Tree Search are combined to produce a powerful reinforcement learning algorithm.
Hopefully you find the AlphaGo Zero cheat sheet useful — let me know if you find any typos or have questions about anything in the document.
If you would like to learn more about how our company, Applied Data Science develops innovative data science solutions for businesses, feel free to get in touch through our website or directly through LinkedIn.
… and if you like this, feel free to leave a few hearty claps :)
Applied Data Science is a London based consultancy that implements end-to-end data science solutions for businesses, delivering measurable value. If you’re looking to do more with your data, let’s talk.